The Pros and Cons of Robot Managers

How would you feel working for a robot? Although the idea may sound far-fetched, not least because the automation of jobs is usually discussed vis-à-vis unskilled labor rather than management-level positions, it is actually more feasible than most people think. Consider some of the main tasks of managers: e.g., using data to evaluate problems, making better decisions than the team, monitoring team members’ performance, setting relevant goals, and providing accurate feedback. Not only is technology capable of rivaling humans on these core management tasks, it is already playing a pivotal role in helping humans to more effectively accomplish these tasks.

In fact, while these basic management tasks may still be a challenge for AI, they are not precisely easy for human managers, either. Workers around the world are disengaged with their jobs, and poor management is a major source of this problem. Even in places where job opportunities abound and unemployment rates are low, people are quitting their jobs to enter self-employment or launch their own business, for it is the best way to avoid having a boss. Academic estimates indicate that 1 in 2 managers will fail in their role, often due to their inability to inhibit their toxic or dark side tendencies. For a quick demonstration of the problem, just Google “my boss is” or “my manager is” to see what most people think of their managers – the autocomplete function will yield a range of traumatic alternatives, accompanied by few or no positives.

It is clear, then, that in the realm of managerial performance, the bar is quite low. It would not require too much for AI to outperform average managers, let alone bad ones. It is as if the automation of drivers would have to outperform a majority of inept drivers, who crash and cause injuries to themselves and others on a regular basis. In this hypothetical scenario (although there are many bad drivers and millions of driving accidents every year, most drivers don’t crash) self-driving cars would not need to be very safe to outperform human drivers.

With this in mind, let us consider the potential pros and cons of automating your manager:

Pros

Avoiding fights. Although technology can make us angry (particularly when it doesn’t work) it is much harder to fight with it than with humans. It takes two to tango. Even if a bot manager had a personality, it would never care enough to engage in a genuine argument with us, for it would lack real emotions. Think about times when your boss irritated you: it was probably due to how s/he felt about something that annoyed you and caused the argument. Conversely, you probably didn’t argue with your computer or TV set when they didn’t work – and you can be sure that they didn’t feel anything about you. Although we are capable of having feelings for technology (good and bad), those feelings are not reciprocated. For all the talk of emotional computing, machines will never give a damn – that is the true reason for their superior intelligence compared to humans; we just care too much, and caring too much can muddle our judgement.

Objective feedback. Although the science of talent management is robust, managers tend to play things by ear. Intuitive decisions invite unconscious (and conscious) biases, creating a nepotistic and political culture where employees feel unfairly treated. Even when their managers are well-intentioned, they are often unable to provide accurate feedback because they’re conflict-averse, jealous, or simply unable to judge employees objectively. To the degree that performance and potential can be quantified (and they can), employees will receive more objective feedback from robots than from human managers.

Better decision making. In an age of information overload, the human brain is incapable of processing the vast sea of data to translate information into knowledge. That’s why Hitachi introduced a computer boss to analyze the best solutions to problems and instruct employees on what to do. This is also why we feel so uninformed these days when we are unable to get online. Of course, some decisions are too complex to automate, but most are probably not. Norbert Wiener, the father of cybernetics, already noted decades ago that “If we can do anything in a clear and intelligible way, we can do it by machine.” In other words, if there is a process, or an algorithm, AI can replicate it and perfect it. The real challenge for AI is replicate unintelligent decisions, that is, “natural stupidity.” Perhaps the ultimate frontier for machine learning is AS – artificial stupidity.

Cons

AI can get it wrong. Algorithms are already making “executive decisions” when they recommend which Uber driver you should avoid, which seller to trust on Amazon, and which news story to believe on Facebook. This is why technology is often defined as “doing more with less”. However, AI is not infallible. For instance, AI’s knowledge that women are underrepresented in senior jobs and that blacks are more likely to be arrested for crimes may lead to advertising high paying jobs to men rather than to women, and to select white job applicants in favor of blacks. In such instances, AI would not be prejudiced, yet its decisions could only be described as sexist and racist, reinforcing rather than combatting human prejudice.

There’s only so much a robot can do. The problem is not that robots cannot do mundane tasks, but that they cannot accomplish some vital ones. For instance, although machines are starting to show signs of creativity, we are a far cry from seeing a robot being entrepreneurial or inventing a new product. Algorithms are able to optimize existing “means and ends” by connecting vast amounts of information at a speed which would be impossible for humans. True innovation, however, is about using information to find new links between means and ends, and involves producing unexpected behaviors. Thus AI can suggest what hotel you should book, but it would not be able to invent AirBnB. Of course, most humans are unable to do that, too. But eliminating the capacity for creativity and innovation in managers would make work even more dull for their employees.

Humans need human contact. Unlike David, the child android in the Steven Spielberg film AI who was programed to love, robots don’t have emotions. Yet, the problem isn’t that “robo-bosses” don’t feel anything; it is that even the most complex machines aren’t sophisticated enough (yet) to detect how you feel. A robot couldn’t understand if you were underperforming because of a cold, or because your dog died. That is also true for human managers, but we are more likely to forgive them than machines, for we can always hope for their empathy. By the same token, employees want recognition and appreciation from other humans rather than AI. Indeed, studies show that human rewards feel far more positive than rewards from machines.

Ultimately, one size does probably not fit all, so it is conceivable that some employees may be more eager to work for a robot than a human manager, particularly those who have been traumatized by their bosses and previous bosses — which, judging from the Google auto-complete exercise above, is an awful lot of people.